Ensemble wind forecasting based on the HARMONIE model and adaptive finite elements in complex orography

[EN]Ensemble forecasting is a methodology to deal with uncertainties in the numerical wind prediction. In this work we propose to apply ensemble methods to the adaptive wind forecasting model presented in. The wind field forecasting is based on a mass-consistent model and a log-linear wind profile using as input data the resulting forecast wind from Harmonie, a Non-Hydrostatic Dynamic model used experimentally at AEMET with promising results. The mass-consistent model parameters are estimated by using genetic algorithms. The mesh is generated using the meccano method and adapted to the geometry…

Study of a wind-wave numerical model and its integration with ocean and oil-spill numerical models

The ability to represent the transport and fate of an oil slick at the sea surface is a formidable task. By using an accurate numerical representation of oil evolution and movement in seawater, the possibility to asses and reduce the oil-spill pollution risk can be greatly improved. The blowing of the wind on the sea surface generates ocean waves, which give rise to transport of pollutants by wave-induced velocities that are known as Stokes’ Drift velocities. The Stokes’ Drift transport associated to a random gravity wave field is a function of the wave Energy Spectra that statistically fully describe it and that can be provided by a wave numerical model. Therefore, in order to perform an accurate numerical simulation of the oil motion in seawater, a coupling of the oil-spill model with a wave forecasting model is needed. In this Thesis work, the coupling of the MEDSLIK-II oil-spill numerical model with the SWAN wind-wave numerical model has been performed and tested. In order to improve the knowledge of the wind-wave model and its numerical performances, a preliminary sensitivity study to different SWAN model configuration has been carried out. The SWAN model results have been compared with the ISPRA directional buoys located at Venezia, Ancona and Monopoli and the best model settings have been detected. Then, high resolution currents provided by a relocatable model (SURF) have been used to force both the wave and the oil-spill models and its coupling with the SWAN model has been tested. The trajectories of four drifters have been simulated by using JONSWAP parametric spectra or SWAN directional-frequency energy output spectra and results have been compared with the real paths traveled by the drifters.

Development of a wake model for wind farms based on an open source CFD solver. Strategies on parabolization and turbulence modeling

Wake effect represents one of the most important aspects to be analyzed at the engineering phase of every wind farm since it supposes an important power deficit and an increase of turbulence levels with the consequent decrease of the lifetime. It depends on the wind farm design, wind turbine type and the atmospheric conditions prevailing at the site. Traditionally industry has used analytical models, quick and robust, which allow carry out at the preliminary stages wind farm engineering in a flexible way. However, new models based on Computational Fluid Dynamics (CFD) are needed. These models must increase the accuracy of the output variables avoiding at the same time an increase in the computational time. Among them, the elliptic models based on the actuator disk technique have reached an extended use during the last years. These models present three important problems in case of being used by default for the solution of large wind farms: the estimation of the reference wind speed upstream of each rotor disk, turbulence modeling and computational time. In order to minimize the consequence of these problems, this PhD Thesis proposes solutions implemented under the open source CFD solver OpenFOAM and adapted for each type of site: a correction on the reference wind speed for the general elliptic models, the semi-parabollic model for large offshore wind farms and the hybrid model for wind farms in complex terrain. All the models are validated in terms of power ratios by means of experimental data derived from real operating wind farms.

Nonlinear models for lateral dynamics of railway vehicles on bridges subject to wind action

The study of lateral dynamics of running trains on bridges is of importance mainly for the safety of the traffic, and may be relevant for laterally compliant bridges. These studies require threedimensional coupled vehicle-bridge models, wheree consideration of wheel to rail contact is a key aspect. Furthermore, an adequate evaluation of safety of rail traffic requires nonlinear models. A nonlinear coupled model is proposed here for vehicle-structure vertical and lateral dynamics. Vehicles are considered as fully three-dimensional multibody systems including gyroscopic terms and large rotation effects. The bridge structure is modeled by means of finite elements which may be of beam, shell or continuum type and may include geometric or material nonlinearities. The track geometry includes distributed track alignment irregularities. Both subsystems (bridge and vehicles) are described with coordinates in absolute reference frames, as opposed to alternative approaches which describe the multibody system with coordinates relative to the base bridge motion. The wheelrail contact employed is a semi-Hertzian model based on realistic wheel-rail profiles. It allows a detailed geometrical description of the contact patch under each wheel including multiple-point contact, flange contact and uplift. Normal and tangential stresses in each contact are integrated at each time-step to obtain the resultant contact forces. The models have been implemented within an existing finite element analysis software with multibody capabilities, Abaqus (Simulia Ltd., 2010). Further details of the model are presented in Antolín et al. (2012). Representative applications are presented for railway vehicles under lateral wind action on laterally compliant viaducts, showing the relevance of the nonlinear wheel-rail contact model as well as the interaction between bridge and vehicle.

The effect of wind and wave action on the mixing and dispersion of wastes /

Mode of access: Internet.

The effectiveness of workplace coaching:A meta-analysis of learning and performance outcomes; scale development; theoretical model of individual differences and longitudinal study

The extant literature on workplace coaching is characterised by a lack of theoretical and empirical understanding regarding the effectiveness of coaching as a learning and development tool; the types of outcomes one can expect from coaching; the tools that can be used to measure coaching outcomes; the underlying processes that explain why and how coaching works and the factors that may impact on coaching effectiveness. This thesis sought to address these substantial gaps in the literature with three linked studies. Firstly, a meta-analysis of workplace coaching effectiveness (k = 17), synthesizing the existing research was presented. A framework of coaching outcomes was developed and utilised to code the studies. Analysis indicated that coaching had positive effects on all outcomes. Next, the framework of outcomes was utilised as the deductive start-point to the development of the scale measuring perceived coaching effectiveness. Utilising a multi-stage approach (n = 201), the analysis indicated that perceived coaching effectiveness may be organised into a six factor structure: career clarity; team performance; work well-being; performance; planning and organizing and personal effectiveness and adaptability. The final study was a longitudinal field experiment to test a theoretical model of individual differences and coaching effectiveness developed in this thesis. An organizational sample of 84 employees each participated in a coaching intervention, completed self-report surveys, and had their job performance rated by peers, direct reports and supervisors (a total of 352 employees provided data on participant performance). The results demonstrate that compared to a control group, the coaching intervention generated a number of positive outcomes. The analysis indicated that coachees’ enthusiasm, intellect and orderliness influenced the impact of coaching on outcomes. Mediation analysis suggested that mastery goal orientation, performance goal orientation and approach motivation in the form of behavioural activation system (BAS) drive, were significant mediators between personality and outcomes. Overall, the findings of this thesis make an original contribution to the understanding of the types of outcomes that can be expected from coaching, and the magnitude of impact coaching has on outcomes. The thesis also provides a tool for reliably measuring coaching effectiveness and a theoretical model to understand the influence of coachee individual differences on coaching outcomes.

Theoretical Performance Model and Initial Experimentation of a Baffled-Tube Ram Accelerator

Thesis (Master's)--University of Washington, 2016-08

Parental involvement in sport: psychometric development and empirical test of a theoretical model

The purposes of the present multistudy were to develop and provide initial construct validity for measures based on the model of parental involvement in sport (Study 1) and examine structural relationships among the constructs of the model (Study 2). In Study 1 (nparents = 342, nathletes = 223), a confirmatory factor analysis was used to verify the psychometric properties of the measures. Content and construct validity were evaluated, as well individual and composite reliability. Multi-group analysis with two independent samples provided evidence of factorial invariance. In Study 2 (nparents = 754, nathletes = 438), structural equation modeling analysis supported the hypothesised model in which athletes’ perceptions of parents’ behaviours mediated the relationship between parents’ reported behaviours and the athletes’ psychological variables conducive to their achievement in sport. The findings provide support for the parental involvement in sport model and demonstrate the role of perceptions of parents’ behaviours on young athletes’ cognitions in sport.

Regional differences of outpatient physician supply as a theoretical economic and empirical generalized linear model

BACKGROUND: Regional differences in physician supply can be found in many health care systems, regardless of their organizational and financial structure. A theoretical model is developed for the physicians' decision on office allocation, covering demand-side factors and a consumption time function. METHODS: To test the propositions following the theoretical model, generalized linear models were estimated to explain differences in 412 German districts. Various factors found in the literature were included to control for physicians' regional preferences. RESULTS: Evidence in favor of the first three propositions of the theoretical model could be found. Specialists show a stronger association to higher populated districts than GPs. Although indicators for regional preferences are significantly correlated with physician density, their coefficients are not as high as population density. CONCLUSIONS: If regional disparities should be addressed by political actions, the focus should be to counteract those parameters representing physicians' preferences in over- and undersupplied regions.

Curvilinear relationships between the job demands-resources (JD-R) model, and work engagement : a police service case study

The current study aims to investigate the non-linear relationship between the JD-R model and work engagement. Previous research has identified linear relationships between these constructs; however there are strong theoretical arguments for testing curvilinear relationships (e.g., Warr, 1987). Data were collected via a self-report online survey from officers of one Australian police service (N = 2,626). Results demonstrated a curvilinear relationship between job demands and job resources and engagement. Gender (as a control variable) was also found to be a significant predictor of work engagement. The results indicated that male police officers experienced significantly higher job demands and colleague support than female officers. However, female police officers reported significantly higher levels of work engagement than male officers. This study emphasises the need to test curvilinear relationships, as well as simple linear associations, when measuring psychological health.

Interpersonal pattern dynamics and adaptive behavior in multiagent neurobiological systems : conceptual model and data

Ecological dynamics characterizes adaptive behavior as an emergent, self-organizing property of interpersonal interactions in complex social systems. The authors conceptualize and investigate constraints on dynamics of decisions and actions in the multiagent system of team sports. They studied coadaptive interpersonal dynamics in rugby union to model potential control parameter and collective variable relations in attacker–defender dyads. A videogrammetry analysis revealed how some agents generated fluctuations by adapting displacement velocity to create phase transitions and destabilize dyadic subsystems near the try line. Agent interpersonal dynamics exhibited characteristics of chaotic attractors and informational constraints of rugby union boxed dyadic systems into a low dimensional attractor. Data suggests that decisions and actions of agents in sports teams may be characterized as emergent, self-organizing properties, governed by laws of dynamical systems at the ecological scale. Further research needs to generalize this conceptual model of adaptive behavior in performance to other multiagent populations.

A hidden Markov model and relative entropy rate approach to vision-based dim target detection for UAV sense-and-avoid

Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.

Theoretical model of user acceptance : in the view of measuring success in web personalization

This paper attempts to develop a theoretical acceptance model for measuring Web personalization success. Key factors impacting Web personalization acceptance are identified from a detailed literature review. The final model is then cast in a structural equation modeling (SEM) framework comprising nineteen manifest variables, which are grouped into three focal behaviors of Web users. These variables could provide a framework for better understanding of numerous factors that contribute to the success measures of Web personalization technology. Especially, those concerning the quality of personalized features and how personalized information through personalized Website can be delivered to the user. The interrelationship between success constructs is also explained. Empirical validations of this theoretical model are expected on future research.